Hitherto, various systems utilizing natural language processing such as automatic translation, voice recognition, document retrieval and document processing, etc. have been put into practical use.
There is shown in FIG. 1 flowchart of outline of processing procedure of a voice translation apparatus according to the prior art as an example of the conventional system.
In the processing procedure of this voice translation apparatus, voice input of step S101 is caused to undergo voice recognition at step S102. Result of that voice recognition is confirmed by user at step S103. When result of voice recognition is recognized by user, recognition result is subjected to machine translation at step S104. If otherwise, processing returns to the step S101 to execute voice recognition for a second time.
Result of machine translation of the step S104 is caused to undergo confirmation by user at step S105. If necessary, editing is implemented thereto at step S106. Synthetic voice (speech) is generated at the last step 107. Thus, this processing procedure is completed.
At stated above, at step S101, user first inputs, to a voice translation unit, conversation that he intends by voice. The voice translation unit carries out recognition of voice inputted at step S102 to display its result. Since erroneous recognition could take place in the voice recognition processing, a processing such that user confirms recognition result is frequently carried out.
As a method of confirming recognition result at step S103, there have been frequently used a method of displaying plural higher rank candidates which have indicated high score in the recognition processing to allow user to select desired one among them, and the like. In the case where sentence that user himself has said is not included in the sentences displayed, sound input is carried out for a second time. When the sentence that user has carried out voice input is decided or established by confirmation of user, that sentence is translated into objective language in turn at step S104.
Since there is the possibility that result including error may be outputted also in the translation processing, there is carried out such a work that user confirms translation result at step S105 for the purpose of maintaining translation accuracy. Further, in the case where translation result is not suitable, editing into representation of suitable objective language is carried out at step S106.
In addition, synthetic voice is generated from translation result and is outputted at step S106. Thus, processing procedure of this voice recognition is completed.
However, in conventional systems utilizing natural language processing, it cannot be said that interface suitable for user is prepared or arranged. For example, in the case of the voice translation unit thus constituted, there are two problems as described below.
First problem is variety of natural languages to be handled and processing accuracy. In the present machine translation, it is very difficult to translate various input sentences with high accuracy. In general, in the machine translation, there exists the problem that according as various sentence styles are handled as input sentences of original or source language, accuracy of translation is lowered to more degree. On the other hand, while restriction is given to sentence style or vocabulary of input sentence, etc., thereby making it possible to improve accuracy of translation, compelling of such input with restriction becomes burden on user. In addition, in the case where there exist polysemy such as meaning or relationship of modification or circumstance dependency, etc. in the input sentence, there generally exist plural results that such input sentence is translated.
In order to univocally specify this, there may be employed either an approach to automatically select suitable candidate on the translation unit side, or an approach to select that candidate by user. However, the former has the problem that erroneous candidate may be selected, and the latter has the problem that it is difficult to select that candidate if user is not familiar with the objective language. In this case, as application of the latter, there may be employed a method of translating translation result into original language for a second tune to present that re-translation result to user to thereby allow him to carry out selection/confirmation. However, there may take place error in the process of re-translation. In addition, in place of presenting translation result, in a method of presenting internal representation of sentence structure tree, etc. or log of process of translation processing, etc., user must know way of finding. Accordingly, selection/confirmation by user is difficult.
The problem applies not only to machine translation processing, but also to all apparatuses utilizing natural language processing such as data base retrieval and/or representation support, etc. by natural language.
The second problem is confirmation work of user. When the processing procedure is viewed from viewpoints of confirmation work of user, user is required to twice carry out confirmation works of result of voice recognition and result of machine translation. Thus, the number of confirmation operations is large. Such a work is troublesome.
This generally applies to systems in which plural modules utilizing natural language processing are combined. For example, let now consider the case where an approach is employed to input Japanese by using kana-kanji conversion to translate it into English by using machine translation. User inputs Japanese sentence by kana to confirm converted Chinese character (kanji) to first generate correct Japanese sentence in which correct kanas and kanjis are mixed. Then, Japanese-English translation is carried out with that Japanese sentence being as input, and user confirms that result for a second time.
In addition, in the case of machine translation, there is the problem that when user is not familiar with objective language, it is very difficult to confirm translated result.